2020 CSDMS meeting-035: Difference between revisions
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|CSDMS meeting city= | |CSDMS meeting city=St. Petersburg | ||
|CSDMS meeting country=United States | |CSDMS meeting country=United States | ||
|CSDMS meeting state= | |CSDMS meeting state=Florida | ||
|CSDMS meeting email address=szeigler@usgs.gov | |CSDMS meeting email address=szeigler@usgs.gov | ||
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|CSDMS meeting abstract=Barrier islands and other coastal landforms are highly dynamic systems, changing in response a spectrum of disturbances from | |CSDMS meeting abstract=Barrier islands and other coastal landforms are highly dynamic systems, changing in response a spectrum of disturbances from multi-decadal ‘press’ disturbances like sea-level rise (SLR) to often more intense episodic perturbations like storms. As a result, multiple stable ecomorphological states exist on barrier islands. In this study, we use a probabilistic Bayesian network approach to investigate the likelihood of shifts among alternative equilibrium states on Fire Island, New York under three scenarios of shoreline change driven by sea-level rise (SLR). Specifically, we highlight areas that are most likely (i) to become inundated, (ii) to shift from one non-inundated state (or landcover type) to another (e.g., a forest becomes beach), or (iii) to remain in the current landcover state. We explore the effects of these changes on the availability of coastal ecosystem types, piping plover habitat, and anthropogenic development. | ||
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Latest revision as of 11:42, 12 February 2020
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Predicted sea-level rise-driven biogeomorphic changes on Fire Island, New York: implications for people and plovers
Sara Zeigler, U.S. Geological Survey St. Petersburg Florida, United States. szeigler@usgs.gov
Erika Lentz, U.S. Geological Survey Woods Hole Massachusetts, United States. elentz@usgs.gov
Benjamin Gutierrez, U.S. Geological Survey Woods Hole Massachusetts, United States. bgutierrez@usgs.gov
Barrier islands and other coastal landforms are highly dynamic systems, changing in response a spectrum of disturbances from multi-decadal ‘press’ disturbances like sea-level rise (SLR) to often more intense episodic perturbations like storms. As a result, multiple stable ecomorphological states exist on barrier islands. In this study, we use a probabilistic Bayesian network approach to investigate the likelihood of shifts among alternative equilibrium states on Fire Island, New York under three scenarios of shoreline change driven by sea-level rise (SLR). Specifically, we highlight areas that are most likely (i) to become inundated, (ii) to shift from one non-inundated state (or landcover type) to another (e.g., a forest becomes beach), or (iii) to remain in the current landcover state. We explore the effects of these changes on the availability of coastal ecosystem types, piping plover habitat, and anthropogenic development.
